Variation in DNA Repair Genes ERCC2, XRCC1, and XRCC3 and Risk of Follicular Lymphoma

Several studies have reported increased risks of non-Hodgkin's lymphoma and chronic lymphocytic leukemia in persons with a history of different types of skin cancer (1-6). Conversely, an increased risk of skin cancer has been noted in patients previously diagnosed with non-Hodgkin's lymphoma (1, 3, 5, 6). These observations fostered the hypothesis that UV radiation exposure is associated with increased risk not only of skin cancer but also of malignant lymphomas. However, this hypothesis, which would have offered an explanation for the epidemic increase in non-Hodgkin's lymphoma incidence observed during the latter half of the 20th century (7), was recently rejected in two large case-control studies (8, 9). Hence, other factors must account for the association between these two malignancies. The observation that non-Hodgkin's lymphoma patients with a previously diagnosed squamous cell skin cancer seem to have a worse prognosis than non-Hodgkin's lymphoma patients without such a history suggests alternative common mechanisms such as alterations in immune function or in capacity to repair DNA (10, 11).

DNA in most cells is regularly damaged by endogenous and exogenous mutagens, and unrepaired damage may lead to unregulated cell growth and cancer (12). Genetic variation in the DNA repair genes ERCC2, XRCC1, and XRCC3 has been associated with altered overall capacity to repair DNA (13-15) and with risk of different types of sporadic skin cancer (16-21). Altered DNA repair function has also been implicated in the development of lung, breast, prostate, bladder, and esophageal cancer (22). The possible role of genetic variation of DNA repair in risk of malignant lymphomas has thus far been little studied in humans (23-25). Only two single nucleotide polymorphisms [SNP; Gln399Arg in the XRCC1 gene (23) and gIVS12-6T>C in the hMSH2 gene (24, 25)] have been evaluated previously in relation to risk of malignant lymphomas overall, with mainly negative results (23, 24).

We recently observed that the association between skin cancer and non-Hodgkin's lymphoma seems to vary by non-Hodgkin's lymphoma subtype and may pertain to follicular lymphoma, but not to, e.g., diffuse large B-cell lymphoma (8). Thus, to further examine the nature of the link between skin cancer and non-Hodgkin's lymphoma, we tested the hypothesis that common variation in the ERCC2, XRCC1, and XRCC3 genes, previously associated with altered DNA repair capacity and skin cancer risk, is associated with susceptibility to follicular lymphoma (a non-Hodgkin's lymphoma subtype specifically associated with skin cancer). The study consisted of 430 patients and 605 controls, included in a large population-based case-control study of non-Hodgkin's lymphoma in Denmark and Sweden.

The proposed candidate genes code for proteins that are involved in three of five recognized DNA repair mechanisms: nucleotide excision repair (ERCC2), base excision repair (XRCC1), and homologous recombination of double-strand breaks (XRCC3; ref. 22). Several of these repair pathways are involved in the restoration of DNA damage induced by exogenous agents such as tobacco smoke and UV radiation (22, 26). As tobacco use has been positively associated with follicular lymphoma (27-29), we hypothesized that effects of this carcinogen on risk of follicular lymphoma may interact with common variation in the studied DNA repair genes. Furthermore, we recently observed that frequent UV radiation exposure was inversely associated with follicular lymphoma risk (8). If DNA repair is at all mechanistically involved in this context is unclear, and perhaps less feasible due to the difference in directions of associations between UV radiation and skin cancer, on one hand, and follicular lymphoma on the other hand. However, to increase our understanding of the enigmatic triad UV radiation-skin cancer-non-Hodgkin's lymphoma, we also examined interaction between sun exposure and DNA repair variants in relation to follicular lymphoma risk.

The present investigation was based on a population-based case-control study in Denmark and Sweden (the Scandinavian Lymphoma Etiology study), which has been described in detail elsewhere (8). In brief, the Scandinavian Lymphoma Etiology study base encompassed the entire population between the ages of 18 and 74 years, living in Denmark from June 2000 to August 2002 and in Sweden from October 1999 to April 2002, with addition of a regional pilot phase in Denmark. The source population was restricted to subjects with sufficient knowledge of the Danish/Swedish language and without history of organ transplantation, HIV infection, or other hematopoietic malignancy. Eligible cases in the Scandinavian Lymphoma Etiology study (all patients with a newly diagnosed non-Hodgkin's lymphoma or Hodgkin's lymphoma) were identified through a rapid case ascertainment network of contact physicians in all hospital departments in both countries where malignant lymphomas are diagnosed and treated. Controls were randomly sampled from the entire Danish and Swedish populations using updated computerized population registers. Subsets of controls were sampled every 6 months during the study period and frequency matched by gender and age (in 10-year intervals) in each country on the expected distribution of non-Hodgkin's lymphoma cases.

Eligible subjects were asked to participate in a telephone interview about possible environmental risk factors for malignant lymphomas and to give blood. The participation rates in the study interview were 83% (n = 3,740) among cases and 71% (n = 3,187) among controls. The interview contained a wide range of questions including anthropometric measures, medical history, medications, and lifestyle. Environmental exposures assessed and tested for gene interaction in the present study included cigarette smoking and UV radiation. Cigarette smoking was classified according to current, former, or never use ∼1 year before lymphoma diagnosis (for cases) or interview (for controls). Subjects who had only used tobacco in other forms were few (n = 35) and were excluded from the stratified analyses. UV radiation exposure measures included total lifetime number of sunbathing vacations abroad and frequency of sun tanning habits during summer in Denmark/Sweden 5 to 10 years before interview (two among several variables describing UV radiation exposure inversely associated with risk of follicular lymphomas in our data; ref. 8). Uniform review of tumor material according to the WHO classification (30) took place within the national lymphoma registry organization (LYFO) in Denmark (31). In Sweden, the review was done by a group of specially appointed expert hematopathologists and cytologists. The study was approved by all regional ethics committees in both countries. Informed consent was obtained from each participant before interview and blood sampling.

Among the interview participants, 85% of the cases (all lymphoma types, n = 3,104) and 65% of the controls (n = 2,072) also gave blood. Blood samples from all cases and approximately every third control in Denmark and every eighth control in Sweden were first centrifugated through a Ficoll density gradient (Axis-Shield UK, Kimbolton, Cambridgeshire, United Kingdom) in Leukosep tubes (Novakemi, Stockholm, Sweden). The separated lymphocytes were then cryopreserved in liquid nitrogen. DNA was isolated from the remaining WBC with the Qiagen Maxi-kit (VWR, Stockholm, Sweden) in both countries and stored at −20°C. The present study included all patients with the specific non-Hodgkin's lymphoma subtype follicular lymphoma who were interviewed in the Scandinavian Lymphoma Etiology study and provided a blood sample (n = 488) and all controls from whom DNA had been prepared during the study period (n = 625). A certain number of the samples were destroyed during storage (n = 63), 4 cases were reclassified as other non-Hodgkin's lymphoma types, and 11 samples failed in quality controls during the genotyping process (see below), leaving 430 cases with follicular lymphoma and 605 population controls for final analysis.

We used a two-step approach for selection of relevant SNPs to assess the genetic variation in the genes. First, we identified validated SNPs (according to genetic databases: http://www.ncbi.nih.gov/) indicated to be associated with sporadic skin cancer (17-21) and with altered overall DNA repair capacity (13-15). Second, we added some validated SNPs, among all identified SNPs with a minor allele frequency of >5%, with the aim of ensuring good marker coverage for haplotype reconstruction (32) and to increase analytic efficiency (minor allele frequency, >5%). These additional SNPs were chosen from public databases (http://www.ncbi.nih.gov/; http://www.hapmap.org/). With this strategy, we selected 35 SNPs in the three genes (12 in ERCC2, 11 in XRCC1, and 12 in XRCC3) for optimization and initial genotyping in 180 samples from Denmark and 180 samples from Sweden (including both cases and controls but with blinding to case or control status). Sixteen SNPs were excluded: eight were found to be monomorphic in our sample, two failed in the Hardy-Weinberg equilibrium test (P < 0.01; ref. 33), and six assays did not show robust results (success rate ≤85%). After removal of the SNPs that did not meet our quality criteria, 19 SNPs (5 in ERCC2, 7 in XRCC1, and 7 in XRCC3; Table 1) were genotyped in the rest of the study subjects.

The DNA samples were genotyped using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (Sequenom, Inc., San Diego, CA; ref. 34). PCR assays and associated extension reactions were designed using the SpectroDESIGNER software (Sequenom) and primers were obtained from Metabion GmbH (Planegg-Martinsried, Germany). All amplification reactions were run under the same conditions in a total volume of 5 μL with 2.5 ng of genomic DNA, 1 pmol of each amplification primer, 0.2 mmol/L of each deoxynucleotide triphosphate, 2.5 mmol/L MgCl₂, and 0.2 units of HotStarTaq DNA polymerase (Qiagen, Crawley, West Sussex, United Kingdom). Reactions were heated at 95°C for 15 minutes, subjected to 45 cycles of amplification (20 seconds at 94°C, 30 seconds at 60°C, 30 seconds at 72°C) before a final extension of 7 minutes at 72°C. Extension reactions were conducted in a total volume of 9 μL using 5 pmol of allele-specific extension primer and the Mass EXTEND Reagents Kit before being cleaned using SpectroCLEANER (Sequenom) on a MULTIMEK 96 automated 96-channel robot (Beckman Coulter, Fullerton, CA). Clean primer extension products were loaded onto a 384-element chip with a nanoliter pipetting system (SpectroCHIP, SpectroJet, Sequenom) and analyzed by a MassARRAY mass spectrometer (Bruker Daltonik GmbH, Bremen, Germany). The resulting mass spectra were analyzed for peak identification using the SpectroTYPER RT 2.0 software (Sequenom). For each SNP, two independent scorers confirmed all genotypes. We used 12 quality control samples for every 384-well plate assay, and none of these failed. In addition, regenotyping of 5% of the study samples resulted in >99% concordance. Hardy-Weinberg calculations were done to ensure that each marker was within allelic population equilibrium in our control sample set (33) and the success rate of each assay was >85%.

Unconditional logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (95% CI) as estimates of relative risk for the single locus genotypes. The logistic regression model included adjustment for the study matching variables age (in 10-year intervals), sex, and country. All analyses were carried out with or without restriction to subjects of Danish/Swedish origin (90%), and, as differences were marginal, results are presented for all subjects. We estimated pairwise linkage disequilibrium values ∣D′∣ and r² (35) and trend tests were done using a likelihood ratio test statistic with 1 degree of freedom. We investigated possible interactions between the a priori chosen environmental exposures and SNP genotypes by introducing multiplicative terms in the regression model. All statistical tests were two sided. Haplotype frequencies were estimated using a model free Expectation-Maximization algorithm proposed for case-control study data when dealing with complex disorders (36). Differences in haplotype distributions between cases and controls were assessed using the global score test statistic described by Schaid et al. (37), which assumes multiplicative penetrance. As the haplotype analyses use more degrees of freedom than single locus analyses, and adjustment of additional covariates also decreases statistical power, we did haplotype analyses both with and without accounting for the study matching factors age, sex, and country. As the matching factors are not likely to be important confounders in analyses of genetic variation, also unadjusted results are of interest. As a secondary analysis, we also did tests of main effects of single loci with adjustment for multiple testing based on the permutation step-down procedure of Westfall and Young (38).

Table 1 provides an overview of genes and SNPs selected for analysis, including rare allele frequencies among the study control subjects. Observed rare allele frequencies were consistent with earlier reports for Caucasian populations for previously investigated polymorphisms (19, 22, 39). Characteristics of the participants are presented in Table 2. Tests for Hardy-Weinberg equilibrium for all of the studied SNPs were carried out and the null hypothesis of Hardy-Weinberg equilibrium was not rejected (α = 0.05) for any of these. Relative risks of follicular lymphoma in relation to studied single locus genotypes are presented in Table 3. Among the controls, we identified eight common (P > 0.01) haplotypes in the ERCC2 gene, five in XRCC1, and four in XRCC3 (Table 4). The average distance between the studied markers was about 4.1 kb in ERCC2, 4.7 kb in XRCC1, and 2.5 kb in XRCC3. In Fig. 1, we give a diagrammatic representation of the genes and polymorphisms investigated along with pairwise ∣D′∣ values for adjacent SNPs. The ∣D′∣ (Fig. 1) and r² (data not shown) values indicated that there was no extensive historical recombination throughout the studied regions. In addition, we calculated r² values for haplotypes (Rh², ref. 40; Table 4), which showed that haplotypes with both low and high frequencies could be well predicted from the unphased data.

In the ERCC2 gene, rare allele heterozygotes of the intron SNPs Rs2070831 and Rs1618536 were at increased risk of follicular lymphoma [OR, 1.9 (95% CI, 1.1-3.2) and OR, 1.5 (95% CI, 1.1-2.1), respectively; Table 3]. However, there were no statistically significant associations between homozygosity of the same rare alleles and follicular lymphoma risk (Table 3). Concerning the XRCC1 gene, we observed no associations between any of the single locus genotypes and risk of follicular lymphoma (Table 3). There were no differences in haplotype distributions, based on the selected polymorphisms, in the ERCC2 or XRCC1 gene between cases and controls either before or after adjustment for the study matching factors (Table 4).

In the XRCC3 gene, rare allele homozygosity of the SNP Rs3212024 in the untranslated 5′ region was statistically significantly associated with follicular lymphoma risk [OR, 1.8 (95% CI, 1.1-2.8); P_trend = 0.05; Table 3]. In addition, rare allele homozygosity of the likewise untranslated Rs3212038 and the Rs3212090 (with intron location) was associated with moderate, borderline statistically significantly increased risk of follicular lymphoma (Table 3). However, in analyses adjusted for multiple testing, these associations no longer reached statistical significance. Using the global score test without any adjustments, there was a statistically significant difference in haplotype distributions of XRCC3 between follicular lymphoma cases and controls (P = 0.02), driven by a higher proportion of cases than controls with the fourth haplotype (TCGTAAC; Table 4). Adjustment for the covariates age, sex, and country rendered the overall difference in haplotype distribution nonsignificant (global test P = 0.1; Table 4) although the case-control difference in proportion carrying the fourth haplotype was still evident (P = 0.04).

There was no evidence of effect modification by cigarette smoking (current/former/never users) in analyses of ERCC2 and XRCC1 single loci. In contrast, for the XRCC3 gene, we observed statistically significant heterogeneity by smoking status for four of seven SNPs (Table 5). In current smokers, homozygotes of the rare alleles of Rs3212024, Rs3212038, or Rs3212090 were all at a >2-fold increased risk of follicular lymphoma compared with homozygotes of the respective common alleles (Table 5). Heterozygotes of the Rs3212068 rare allele were at a 70% reduced risk. In former smokers, the same associations were weaker and no associations could be observed among never smokers (Table 5). When the XRCC3 haplotype analysis was stratified on smoking status, the evidence of a genetic association related to smoking status was weakened (data not shown). However, the rare alleles associated with follicular lymphoma in current smokers in the single loci analyses (Rs3212024, Rs3212038, and Rs3212090) seemed to be only on one and the same common haplotype; thus, the haplotype analysis did not add weight to the findings of the reported SNP analysis but used more degrees of freedom. Further, we investigated possible interaction between the studied SNPs and exposure to UV radiation. However, we found no evidence of interaction between UV radiation exposure measures and any of the analyzed single loci in relation to follicular lymphoma risk (data not shown).

This study provides no evidence of a role of common variation in the DNA repair genes ERCC2 and XRCC1 in susceptibility to follicular lymphoma. However, our data indicated that variation in the XRCC3 gene may be of relevance to follicular lymphoma risk, perhaps mainly in cigarette smokers. Associations with follicular lymphoma risk were observed for three specific SNPs, all located in areas with unknown functional significance. However, as these three polymorphisms were strongly linked, it remains unclear if any true association is due to the identified markers or to other unidentified genetic susceptibility loci belonging to the same haplotype. The hypothesis of a link between skin cancer and follicular lymphoma due to common variation in these genes was not supported. The observed associations for XRCC3 were too weak to explain an ∼2-fold increased risk of follicular lymphoma in subjects with a history of skin cancer (8). In addition, previous reports more strongly indicate associations between sporadic skin cancer and polymorphic variation in the ERCC2 and XRCC1 genes than in XRCC3 (21, 39). Furthermore, our findings seemed to be confined to cigarette smokers, a group at increased risk of squamous cell carcinoma of the skin, but not of basal cell carcinoma (the most common type of skin cancer) or malignant melanoma (41), whereas all three skin cancer types have been associated with an excess risk of non-Hodgkin's lymphoma.

Three previous studies have investigated the role of DNA repair genes in relation to susceptibility of malignant lymphomas (23-25). Each of these studies was restricted to analysis of one SNP in one gene and risk of malignant lymphomas or non-Hodgkin's lymphoma overall [Arg→Gln in XRCC1 (Rs25487): no association (23); gIVS 12-6T→C of the hMSH2 gene: no association in one study (24) and a positive association in one (25)]. Consequently, there was no possibility to assess associations with haplotypes nor was there any information on environmental exposures. Although our negative results for XRCC1 were consistent with the findings of Matsuo et al. (Rs25487; ref. 23), comparisons were limited by hospital-based sampling of controls and study subjects belonging to a different ethnic group in that study.

Strengths of our investigation included the population-based design, the relatively large study size considering the restriction to one specific non-Hodgkin's lymphoma subtype, and the ethnic homogeneity of the Danish and Swedish populations. Population stratification is a concern in studies of genetic susceptibility as the ancestral ethnicity mix of cases and controls may differ and result in genotype differences unrelated to disease. The fact that our results did not vary by country and remained essentially unchanged when the analyses were restricted to subjects with both parents born in Denmark or Sweden indicates that this is not a major concern. Differences in blood donation rates between initially eligible cases (70%) and controls (50%) in the founding case control study could have introduced a selection bias. However, it is unlikely that nonparticipation would be directly associated with common variation in DNA repair genes as the corresponding phenotypes are subtle if at all clinically evident. Chance may explain the indications of increased risks with several XRCC3 single loci genotypes and follicular lymphoma risk overall, especially considering the large number of analyses done and the weak evidence of a difference in haplotype distributions. However, it is more difficult to attribute to chance alone the indication of interaction with smoking status and several XRCC3 single loci belonging to one haplotype.

Another strength of our study was the haplotype-based approach, which is recognized as a more comprehensive way of describing the genetic variation over genome segments for individuals (32, 33, 42). With the genotyped SNPs, we are likely to have distinguished all major haplotypes with frequencies of >5% according to HapMap data (http://www.hapmap.org), and thus to have captured most ancient, common variation within the candidate genes, allowing us to draw conclusions about their relative risk effects within the limits of the power of our sample size. However, a relatively low density of genotyped markers in a few regions may have limited our ability to capture all variation. In addition, the usefulness of haplotypes in terms of achieving power to detect associations is questionable when small genomic areas in which linkage disequilibrium is strong are being studied (43), although in this case the haplotypes were well predicted by the genotyped SNPs.

Little is known about specific risk factors (and markers of susceptibility) for follicular lymphoma although strong primary or acquired immune suppression is the most well-established risk factor for non-Hodgkin's lymphoma overall. Tobacco smoking has been suggested to increase risk of follicular lymphoma (27, 29). Interestingly, tobacco use seems to induce the chromosomal translocation t(14;18) in peripheral lymphocytes of healthy individuals (44), a translocation which is also found in 70% to 95% of follicular lymphoma tumors (30). Our observations support a possible role of cigarette smoke in the development of follicular lymphoma in susceptible individuals carrying a specific XRCC3 haplotype. As tobacco smoke carcinogens induce different types of DNA damage, the repair of which involves several repair pathways, one could have expected to find evidence of a similar effect modification by tobacco use for ERCC2 and XRCC1 genotype variants as well in our data. However, the genes selected for the present analysis may not correctly reflect the importance of the different DNA repair pathways in this context. Furthermore, a smoking-independent effect of common variation in the XRCC3 gene on the development of follicular lymphomas could be possible through the hypermutation machinery. Follicular lymphomas arise from lymphoid tissue germinal centers where maturating lymphocytes undergo somatic hypermutation in the immunoglobulin variable-region genes to enhance antibody affinity for specific antigens (30). Evidence suggests that the XRCC3 gene product takes part in this hypermutation process (45).

We did not observe any statistically significant interaction between measures of UV radiation exposure and investigated polymorphic variants in relation to risk of follicular lymphoma. Although the observed inverse association between UV radiation and follicular lymphoma risk (8) could, in theory, be mediated through systemic immune modulation initiated by DNA repair–dependent, UV-specific DNA damage (46), these results give indirect support for alternative explanatory mechanisms such as for example vitamin D. To conclude, our results indicate that polymorphic variants and haplotypes of the XRCC3 gene may be associated with risk of follicular lymphoma, especially in current cigarette smokers. Thus, this common carcinogen may be of importance for lymphomagenesis in susceptible individuals. Although our results are suggestive and need confirmation in additional independent studies, they point to a potentially important mechanism for follicular lymphoma susceptibility. There was further little to suggest that the association between skin cancer and follicular lymphoma is mediated through polymorphic variation of the investigated DNA repair genes. However, as DNA repair mechanisms are complex and a number of proteins interact in each of the five recognized DNA repair pathways (22), common variation in other DNA repair genes may still contribute to an association between the two malignancies. Assessment of variation in interrelated genes, gene-gene interaction in and between different pathways, and/or direct measurement of DNA repair capacity is necessary to fully evaluate a potential role of DNA repair in the development of follicular lymphoma.

We thank Charlotte Appel (Statens Serum Institut), Leila Nyrén (Karolinska Institutet), and Kirsten Ehlers at LYFO for project coordination and data collection; cytologist Edneia Tani and pathologists Anna Porwit-MacDonald (Karolinska University Hospital, Stockholm), Måns Åkerman (Lund University Hospital), Åke Öst (Medilab, Stockholm), and Christer Sundström (Akademiska Hospital, Uppsala) for extensive review of tumor material; Randi Paynter for help with the genetic diagram; and all contact doctors and nurses in Denmark and Sweden who participated in our rapid case ascertainment system.